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<p>Glioblastoma is a lethal primary brain tumor with poor prognosis. Tumor cells exhibit substantial phenotypic variation, complicating treatment. As functional diversity is driven by underlying transcriptional states, characterizing tumor cell gene expression is essential for understanding tumor biology and therapeutic response. The GL261 tumor cell line is a common pre-clinical model system for investigating glioblastoma pathobiology. However, global gene expression patterns in this model are unknown. Here we describe the use of single-cell RNA sequencing (scRNA-Seq) to investigate transcriptional profiles of 5764 adherent and 4951 neurosphere GL261 cells, generating 133,442,221 sequenced reads. Following Principal Component Analysis (PCA) for dimensionality reduction, we applied Uniform Manifold Approximation and Projection (UMAP) to visualize transcriptionally distinct subpopulations (clusters) of GL261 cells grown adherently or as neurospheres. Highly expressed and differentially expressed genes were identified. Because the neurosphere phenotype is known to be more tumorigenic, we further examined differentially expressed genes with gene ontology expression analysis. We found that upregulated genes in neurosphere cells are associated with angiogenesis, cell adhesion, and cell signaling pathways. In addition, we specifically examined gene expression patterns of matrix metalloproteinases and purinergic receptors, glioblastoma drug targets known to be important for promoting tumor infiltration into adjacent healthy tissue. We found that P2RX7, MMP15 and MMP16 are upregulated in neurosphere cells, indicating a potential role for these genes in tumor formation. Together these results reveal global transcriptional profiles of GL261 cells, establish a resource for further scRNA-Seq-based analyses, and give insight into gene expression changes relevant to glioblastoma tumor development.</p>

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Single-Cell Transcriptomic Profiling of GL261 Glioblastoma Cells Reveals Gene Expression Signatures Underlying Tumorigenicity

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月16日

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  • Colton E. Troxel,
  • Ruby A. Olvera,
  • Emily A. Freko,
  • Suely S. C. Soeiro,
  • Thandiswa T. Mdluli,
  • Richard L. Daniels

摘要

Glioblastoma is a lethal primary brain tumor with poor prognosis. Tumor cells exhibit substantial phenotypic variation, complicating treatment. As functional diversity is driven by underlying transcriptional states, characterizing tumor cell gene expression is essential for understanding tumor biology and therapeutic response. The GL261 tumor cell line is a common pre-clinical model system for investigating glioblastoma pathobiology. However, global gene expression patterns in this model are unknown. Here we describe the use of single-cell RNA sequencing (scRNA-Seq) to investigate transcriptional profiles of 5764 adherent and 4951 neurosphere GL261 cells, generating 133,442,221 sequenced reads. Following Principal Component Analysis (PCA) for dimensionality reduction, we applied Uniform Manifold Approximation and Projection (UMAP) to visualize transcriptionally distinct subpopulations (clusters) of GL261 cells grown adherently or as neurospheres. Highly expressed and differentially expressed genes were identified. Because the neurosphere phenotype is known to be more tumorigenic, we further examined differentially expressed genes with gene ontology expression analysis. We found that upregulated genes in neurosphere cells are associated with angiogenesis, cell adhesion, and cell signaling pathways. In addition, we specifically examined gene expression patterns of matrix metalloproteinases and purinergic receptors, glioblastoma drug targets known to be important for promoting tumor infiltration into adjacent healthy tissue. We found that P2RX7, MMP15 and MMP16 are upregulated in neurosphere cells, indicating a potential role for these genes in tumor formation. Together these results reveal global transcriptional profiles of GL261 cells, establish a resource for further scRNA-Seq-based analyses, and give insight into gene expression changes relevant to glioblastoma tumor development.